Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Type D and Type F activities
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea magistrale in Management e strategia d’impresa - Enrollment from 2025/2026The didactic plans of each course of study provide for the obligation to obtain a certain number of credits through optional activities (also called 'type D and F').
In addition to teaching provided for in the didactic plans of other courses and language or IT certifications as specified in the regulations of each course, these activities may also consist of extracurricular initiatives of various contents, such as, for example, participation in a seminar or a series of seminars, attendance at teaching workshops, carrying out project work, additional internships, etc.
As with any other elective activity, these must be consistent with knowledge and skills already acquired by the student.
Those listed on this page are the extracurricular initiatives that the Teaching Commission has approved and, therefore, allow those who take part in them to acquire the specified credits, subject to the conditions set out on the detail pages of each initiative.
In this regard, please note that:
- all these initiatives require, for the acquisition of the relative CFUs, the passing of a test to verify the skills acquired, following the indications contained in the 'Examination methods' section of the individual activity
- the student must include the chosen activity in his or her study plan and enrol in the roll specifically created for the test, the date of which is set by the teacher of reference and published in the 'Examination methods' section of the individual activity.
SOFT SKILLS
Discover the training courses promoted by the University's Teaching and Learning Centre for students enrolled on degree courses aimed at promoting soft skills: https://talc.univr.it/it/competenze-trasversali
CONTAMINATION LAB
The Contamination Lab Verona (CLab Verona) is an experiential pathway with modules dedicated to innovation and enterprise culture that offers the opportunity to work in teams with students from all degree courses to solve challenges set by companies and organisations. The pathway allows you to receive 6 CFUs in D or F. Discover the challenges: https://www.univr.it/it/clabverona
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WARNING: To be admitted to any teaching activity, including those of your choice, you must be enrolled in the course year in which it is offered. Graduands in the December and April sessions are therefore advised NOT to undertake extracurricular activities in the new academic year in which they are not enrolled, as these sessions are valid for the previous academic year. Therefore, no CFU recognition will be granted for activities carried out in an academic year in which they are not enrolled.
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | B-education: Sound ideas | D |
Cristina Florio
(Coordinator)
|
| 1° 2° | B-education: Sound ideas | D |
Cristina Florio
(Coordinator)
|
| 1° 2° | Ciclo tematico di conferenze “Italia nel mondo” - 2024/2025 | D |
Riccardo Stacchezzini
(Coordinator)
|
| 1° 2° | Ethical finance | D |
Giorgio Mion
(Coordinator)
|
| 1° 2° | Generative AI (Artificial Intelligence) for Business Communication | D |
Massimo Melchiori
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Methods and tools for literature reviews | D |
Cristina Florio
(Coordinator)
|
| 1° 2° | Experience 3 Days as a Manager | D |
Nicola Cobelli
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Data Analysis Laboratory with R (Vicenza) | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Data Visualization Laboratory | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Python Laboratory | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Data Science Laboratory with SAP | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Advanced Excel Laboratory (Vicenza) | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Excel Laboratory (Vicenza) | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Methods and tools for empirical research in management | D |
Nicola Cobelli
(Coordinator)
|
| 1° 2° | Methods and tools for empirical research in management | D |
Nicola Cobelli
(Coordinator)
|
| 1° 2° | Plan your professional future | D |
Paolo Roffia
(Coordinator)
|
| 1° 2° | Plan your professional future | D |
Paolo Roffia
(Coordinator)
|
| 1° 2° | Marketing plan | D |
Fabio Cassia
(Coordinator)
|
| 1° 2° | Programming in Matlab | D |
Marco Minozzo
(Coordinator)
|
| 1° 2° | Programming in SAS | D |
Marco Minozzo
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Artificial Intelligence, AI and Business Operations: Methods and Techniques | D |
Lapo Mola
(Coordinator)
|
| 1° 2° | The business consultant accountant | D |
Riccardo Stacchezzini
(Coordinator)
|
| 1° 2° | Relational soft skills for professional presence | D |
Federico Brunetti
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Soft skills coaching days | D |
Paola Signori
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | French B1 | D | Not yet assigned |
| 1° 2° | French B2 | D | Not yet assigned |
| 1° 2° | English C1 | D | Not yet assigned |
| 1° 2° | Russian B1 | D | Not yet assigned |
| 1° 2° | Russian B2 | D | Not yet assigned |
| 1° 2° | Spanish B1 | D | Not yet assigned |
| 1° 2° | Spanish B2 | D | Not yet assigned |
| 1° 2° | German B1 | D | Not yet assigned |
| 1° 2° | German B2 | D | Not yet assigned |
Statistics for Business (2024/2025)
Teaching code
4S008094
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
SECS-S/03 - ECONOMIC STATISTICS
Period
Primo semestre LM dal Sep 30, 2024 al Dec 23, 2024.
Courses Single
Authorized
Learning objectives
The course aims to provide the basic knowledge for the collection, management and analysis of data of interest in the managerial field. Students' previous statistical knowledge will be integrated with the main statistical sampling techniques for data collection, some of the most widespread techniques for the analysis of time series data, the multiple linear regression, and the most recent techniques for data science in the business context. All these techniques will be discussed in specific areas of application: market research, customer analysis, management control, production process control, sales analysis and forecasting. Special attention will be devoted to some of the most widespread software for data science and business intelligence. At the end of the course, students should demonstrate a good level of understanding both theoretically and practically of the main statistical methods for the analysis of business phenomena, in the light of the available data and the managerial needs. They should also be able to interpret critically the gathered information and the results obtained from the analyses with the aim to supply useful suggestions in support of business decisions.
Prerequisites and basic notions
The basic notions of statistics studied in the three-year degree courses in economics are taken for granted. In any case, the teacher will provide a handout with the treatment of the main topics of Statistics that will be used in this course. This handout will be an integral part of the course and the exam
Program
Business Statistics Data Sources Sampling Linear Regression Mutability and Pareto Analysis Concentration and the Lorenz Curve Statistical Quality Control Choosing Business Investments Under Uncertainty Benford's Law and Preventing Corporate Fraud Introduction to Microsoft Power BI Software
Didactic methods
The lessons will be held in person at the time indicated in the appropriate space on the site. The content of the lessons will be recorded and the recordings will be available on the Moodle platform of the course. The participatory teaching activities will be carried out in the classroom and may, by their nature, not be recordable. The following is specified: 1) the exercises will be carried out by the teacher in class also with the aid of Personal Computers. It is recommended to participate in the exercises with the personal PC in order to be able to upload the files provided in advance and perform the analysis of the data contained therein 2) the introduction to the Microsoft Power BI software is intended to provide the student with the first basic knowledge to then independently study this now essential tool for analyzing business data. The teacher will provide example data on which useful reports will be derived and built in the business field
Learning assessment procedures
The exam consists of a written test on the entire program lasting two hours.
Evaluation criteria
Ability to understand problems and analyze them by choosing and applying the appropriate statistical method.
Criteria for the composition of the final grade
The written test is structured as follows: 1) 9 multiple choice questions regarding theoretical aspects of the program covered (up to 9 points out of 30) 2) 3 exercises with numerical calculations of applications to concrete cases of the analysis techniques learned during the course (up to 21 points out of 30) The student may submit before the end of the lessons an in-depth work using the Microsoft Power BI software which, if considered valid by the teacher, will lead, in the event of a sufficient evaluation of the exam, to an increase in the evaluation of up to 2 points. The software can be downloaded free of charge.
Exam language
Italiano
